The present invention relates to medical diagnostic ultrasonic imaging, and in particular to methods and systems for suppressing electronic noise in such imaging.
Due to the finite penetration depth of acoustic waves in ultrasound imaging, the ultrasound image is often dominated by electronic noise in the far field. Electronic noise also dominates in regions of low echogenicity such as in blood pools.
Several approaches have been used in the past in an attempt to reduce electronic noise in ultrasonic imaging. One approach is to provide the user with manually adjustable depth gain controls. The user can then use these controls to reduce electronic noise in the far field. However, manual optimization of an image to reduce electronic noise is inconvenient, and the effectiveness of such manual optimization is highly dependent on the skills of the user. Furthermore, such manual optimization provides only an average adjustment constrained by the size of the independently adjustable zones, and depth gain controls do not allow two-dimensional variations of gain in order to suppress noise in a subregion having irregular boundaries.
Another prior-art approach is to apply temporal persistence to reduce the visual effect of electronic noise. However, temporal persistence will cause blurring of the image whenever there is motion between the transducer and the imaged tissue.
A third prior-art approach is to limit the maximum gain applied by the imaging system. This approach brings with it a concomitant loss in the maximum penetration depth.
A fourth approach is described in Kim U.S. Pat. No. 5,653,234, in which a single line of acoustic ultrasound data is processed to determine an SNR or rate of change parameter. This parameter is then used to adjust the pass band of a low-pass filter to reduce noise. The disclosed system operates on only one-dimensional (range-varying) signals prior to detection.
The present invention is directed to an improved method and apparatus that automatically determine regions of the image dominated by electronic noise and modify image processing for such regions to improve the resulting image.
By way of introduction, the embodiments described below provide an SNR-adaptive method for processing a plurality of post-detection ultrasonic images. A cross-correlation parameter is determined from corresponding multi-dimensional regions of at least two post-detection ultrasonic images, and the cross-correlation parameter is then used to suppress electronic noise in ultrasonic image processing. For example, the cross-correlation parameter can be used to adjust a weighting factor that controls gain on a pixel-by-pixel basis, or to adjust the bandwidth of a low-pass filter applied to an ultrasonic image signal. In order to improve the determination of the cross-correlation parameter in the event of tissue motion, the multi-dimensional regions that are to be cross-correlated can be registered to compensate for relative motion between the transducer and the imaged tissue that occurs between the cross-correlated images.
The foregoing paragraph has been provided by way of introduction, and is not intended to limit the scope of the following claims.